Paper Authors

Walter McDonald
Virginia Tech

Walter McDonald is a Ph.D. Student, jointly advised by Drs. Dymond and Lohani, in the CEE program at Virginia Tech with a focus in water-resources engineering. He received a B.S. in civil engineering from Texas Tech University and a M.S. in civil engineering from Texas A&M University. He has had extensive training in hydrology and currently works in the LEWAS lab, where he conducts water-sustainability research. He has also developed and implemented curricula for introducing the LEWAS into freshman-level courses at Virginia Western Community College and a senior level hydrology course at Virginia Tech.

Daniel S Brogan
Virginia Tech

Daniel S. Brogan is a PhD student, advised by Dr. Lohani, in Engineering Education with BS and MS degrees in Electrical Engineering. He has completed several graduate courses in engineering education pertinent to this research. He is the key developer of the OWLS and leads the LEWAS lab development and implementation work. He has mentored two NSF/REU Site students in the LEWAS lab. He assisted in the development and implementation of curricula for introducing the LEWAS at VWCC including the development of pre-test and post-test assessment questions. Additionally, he has a background in remote sensing, data analysis and signal processing from the University of New Hampshire.

Vinod K Lohani
Virginia Tech

Randel L. Dymond
Virginia Tech

Dr. Randy Dymond is an Associate Professor of Civil and Environmental Engineering at Virginia Tech. With degrees from Bucknell and Penn State, Dr. Dymond has more than 30 years of experience academics, consulting, and software development. He has taught at Penn State, the University of Wisconsin-Platteville, and has been at Virginia Tech for 17 years. Dr. Dymond has published more than 60 refereed journal articles and proceedings papers, and been the principal or co-principal investigator for more than 120 research proposals from many diverse funding agencies. His research areas include urban stormwater modeling, low impact development, watershed and floodplain management, and sustainable land development. Dr. Dymond has had previous grants working with the Montgomery County Public Schools and with the Town of Blacksburg on stormwater research and public education. He teaches classes in GIS, land development, and water resources and has won numerous teaching awards, at the Departmental, College, and National levels.

Abstract

Assessing Cognitive Development and Motivation with the Online Watershed Learning System (OWLS)A recent report on Challenges and Opportunities in the Hydrologic Sciences by the NationalAcademy of Sciences states that the solutions to the complex water-related challenges facingsociety today begin with education. The Learning Enhanced Watershed Assessment System(LEWAS) is a real-time watershed monitoring lab that seeks to address these complex-waterrelated challenges by improving water-related education at the community college and four yearuniversity levels. The Online Watershed Learning System (OWLS), the data sharing andvisualization component of the LEWAS, is an environmental exploration tool that gives usersaccess to historical and live LEWAS data, watershed-specific case studies, and virtual tours ofthe LEWAS watershed. By using an HTML5-driven web interface, the OWLS interactivelydelivers integrated live and/or historical remote system data (visual, environmental,geographical, etc.) to end users regardless of the hardware (desktop, laptop, tablet, smartphone,etc.) and software (Windows, Linux, iOS, Android, etc.) platforms of their choice..We have built upon a prior study that used the expectancy-value theory of motivation to showthat exposure to live watershed data via the LEWAS increased students’ levels of motivation. Apilot test of the OWLS has demonstrated positive learning gains in engineering seniors and wasoverwhelmingly viewed by students as having helped them learn hydrology concepts. The pilottest also revealed the strengths of the OWLS to be anywhere, anytime access to live system dataand interactive graphical representations of the data. Using the framework of situated learning,the current research implements the OWLS as a remote lab for both freshmen community collegestudents in general engineering courses as well as senior university students in a hydrologycourse. We seek to determine: (i) how the OWLS influences student learning with respect tocourse learning objectives, and (ii) how the use of OWLS in engineering courses impactsmotivation in students. The assessment follows an experimental design with pre- and post-testquestions that include both Likert-style motivation questions and concept inventory-stylecognitive learning questions that have been developed by content experts for each course leveland are scaled using Bloom’s Revised Cognitive Taxonomy. Results from fall 2014 freshmencourses and from both levels in the spring 2015 semester will be analyzed and presented.

EndNote - RIS

TY - CPAPER
AB - Assessing Cognitive Development and Motivation with the Online Watershed Learning System (OWLS)A recent report on Challenges and Opportunities in the Hydrologic Sciences by the NationalAcademy of Sciences states that the solutions to the complex water-related challenges facingsociety today begin with education. The Learning Enhanced Watershed Assessment System(LEWAS) is a real-time watershed monitoring lab that seeks to address these complex-waterrelated challenges by improving water-related education at the community college and four yearuniversity levels. The Online Watershed Learning System (OWLS), the data sharing andvisualization component of the LEWAS, is an environmental exploration tool that gives usersaccess to historical and live LEWAS data, watershed-specific case studies, and virtual tours ofthe LEWAS watershed. By using an HTML5-driven web interface, the OWLS interactivelydelivers integrated live and/or historical remote system data (visual, environmental,geographical, etc.) to end users regardless of the hardware (desktop, laptop, tablet, smartphone,etc.) and software (Windows, Linux, iOS, Android, etc.) platforms of their choice..We have built upon a prior study that used the expectancy-value theory of motivation to showthat exposure to live watershed data via the LEWAS increased students’ levels of motivation. Apilot test of the OWLS has demonstrated positive learning gains in engineering seniors and wasoverwhelmingly viewed by students as having helped them learn hydrology concepts. The pilottest also revealed the strengths of the OWLS to be anywhere, anytime access to live system dataand interactive graphical representations of the data. Using the framework of situated learning,the current research implements the OWLS as a remote lab for both freshmen community collegestudents in general engineering courses as well as senior university students in a hydrologycourse. We seek to determine: (i) how the OWLS influences student learning with respect tocourse learning objectives, and (ii) how the use of OWLS in engineering courses impactsmotivation in students. The assessment follows an experimental design with pre- and post-testquestions that include both Likert-style motivation questions and concept inventory-stylecognitive learning questions that have been developed by content experts for each course leveland are scaled using Bloom’s Revised Cognitive Taxonomy. Results from fall 2014 freshmencourses and from both levels in the spring 2015 semester will be analyzed and presented.
AU - Walter McDonald
AU - Daniel S Brogan
AU - Vinod K Lohani
AU - Randel L. Dymond
CY - Seattle, Washington
DA - 2015/06/14
PB - ASEE Conferences
TI - Assessing Cognitive Development and Motivation with the Online Watershed Learning System (OWLS)
UR - https://peer.asee.org/23577
DO - 10.18260/p.23577
ER -